ABSTRACT
Background
Managing postoperative pain while minimising opioid‐related adverse drug events (ORADEs) remains a clinical challenge. The OPIAID Zone Tool is a visual scoring system designed to evaluate pain and ORADEs together. It has pain on the x‐axis and ORADEs on the y‐axis and categorises patients into zones of increased combined symptom burden. We aimed to evaluate the OPIAID Zone Tool, assess its association with postoperative outcomes and explore alternative versions.
Methods
This prospective observational cohort pilot study included 145 adult patients undergoing orthopaedic and abdominal surgery under general anaesthesia with postoperative care in the post‐anaesthesia care unit at Bispebjerg Hospital, Denmark. The primary outcome was the OPIAID Zone Tool score (version 0.5). Secondary analyses assessed associations with patient‐perceived health (EQ‐VAS), quality of recovery (QoR‐PACU) and time to discharge readiness in PACU, evaluated using R 2, AIC and BIC.
Results
Distribution across OPIAID Zones was broad (Zone 0: 13.8%, Zone 1: 6.9%, Zone 2: 22.1%, Zone 3: 18.6%, Zone 4: 20.0%, Zone 5: 18.6%), without clear clustering and with a tendency towards pain‐dominant profiles. The OPIAID Zone Tool score was significantly associated with EQ‐VAS (R 2 = 0.39), QoR‐PACU (R 2 = 0.35) and PACU discharge readiness (R 2 = 0.50), showing stronger overall associations than pain and ORADEs assessed separately.
Conclusion
The OPIAID Zone Tool (version 0.5) combines pain and ORADE scores into a single metric while simultaneously visualising their distribution across the population. The Zone score was associated with patient‐centred outcomes and outperformed pain and ORADEs assessed separately, though a risk of overfitting cannot be ruled out. Further refinement and prospective validation are planned to optimise the tool and confirm its clinical utility.
Editorial Comment
How high is the quality of the early postoperative analgesia that is being delivered? This study presents a model and instrument for quantifying quality of early postoperative analgesia combining treatments, pain reporting and opioid‐related adverse events. The performance of the new instrument is presented with associations to recovery scores and time to post‐anaesthesia unit discharge.
1. Background
As part of perioperative pain management, opioids are commonly administered both prophylactically to reduce postoperative pain and as rescue analgesia. However, increasing opioid doses are associated with a higher risk of opioid‐related adverse drug events (ORADEs) [1]. Currently, pain and ORADEs both occur frequently (10%–40%) immediately after surgery [2, 3, 4]. Both are associated with impaired quality of recovery and worse long‐term outcomes [5, 6, 7, 8]. Accordingly, pain and ORADEs are central outcomes in both clinical quality monitoring [9] and perioperative research [10].
Different perioperative analgesic strategies result in different trade‐offs between postoperative pain and ORADEs. This balance is influenced by the use of non‐opioid analgesics, regional anaesthesia techniques and the choice of restrictive or liberal opioid administration. The overall aim is to minimise both moderate‐to‐severe pain and ORADEs, recognising that improvements in one outcome may come at the expense of the other. Thus, assessing both the individual contributions of pain and ORADEs and their combined burden may improve the evaluation of perioperative pain management.
In clinical trials, reporting these outcomes separately can complicate interpretation. For example, an intervention may improve pain control but increase ORADEs, whereas the comparator may result in the opposite, making it difficult to identify the optimal analgesic strategy [11, 12]. Although composite quality‐of‐recovery scales exist and are valuable in many contexts, they capture broader domains of recovery, including aspects such as the quality of information provided by healthcare staff, mobilisation and other outcomes [13]. These tools typically produce a single summary score without indicating, visually or otherwise, whether opioid dosing is appropriate, excessive or insufficient at either the individual or population level. Pain control, ORADEs and opioid use are typically reported as separate outcomes in the literature, with limited integration across these domains [14, 15, 16].
We developed the OPIAID Zone Tool to combine pain and ORADE burden without concealing their separate contributions. The tool integrates patient‐reported pain (x‐axis) and ORADEs (y‐axis) and patients are stratified into different OPIAID zones with increasing combined burden. By visualising the combined distribution of pain and ORADEs across these zones, the tool aims to identify whether there is an issue with pain management within a population and, if so, whether the main clinical challenge is primarily driven by inadequate analgesia, by ORADEs or by a balanced burden.
In this study, we aimed to explore and describe the OPIAID Zone Tool in a prospective cohort. We hypothesised that the tool would demonstrate stronger associations with quality of recovery, patient‐perceived health status and time to discharge readiness from the post‐anaesthetic care unit (PACU) than pain intensity and ORADEs separately. Furthermore, we exploratively aimed to use the cohort data to identify potential refinements of the tool before prospective external validation.
2. Methods
In this protocolised [17] prospective cohort study, we included a convenience sample of 145 adult (≥ 18 years) patients undergoing seven surgical procedures in general anaesthesia that required a stay in a PACU irrespective of pain and ORADE severity. The study was approved by the Capital Region of Denmark and written informed consent was obtained from all subjects.
2.1. Eligibility
Included procedures were laparoscopic cholecystectomy, laparoscopic colorectal resection, laparoscopic appendectomy, inguinal and femoral hernial repair, trochleoplasty, elective total hip arthroplasty, hip arthroscopy, total knee arthroplasty and anterior cruciate ligament reconstruction. Patients receiving peripheral nerve blocks were eligible for inclusion, as these procedures were selected because adequate perioperative analgesia cannot generally be achieved with peripheral nerve blocks alone. Patients receiving neuraxial anaesthesia and opioid‐tolerant patients (defined as a daily opioid intake > 30 mg oral morphine equivalents for at least 7 days up to surgery) were excluded [18].
2.2. Data Collection
Patients were assessed in the PACU at Bispebjerg Hospital on specific days of inclusion between 15 March 2024 and 1 August 2024. The total number of patients who underwent surgery at the hospital, along with the number of eligible and included patients, was recorded on each of these inclusion days.
Data were extracted from the electronic patient chart SundhedsPlatformen (EPIC Systems Corporations, WI, USA) and during patient assessments into an electronic database, REDCap (Vanderbilt University, TN, USA). We collected relevant data from the electronic patient chart during hospitalisation (Table S1). The investigator (T.X.M.T.) managed all follow‐up assessments in the surgical ward and by telephone.
2.3. Permissions
The Danish National Center for Ethics concluded that the study did not require ethical approval (F‐23064248; 24 October 2023). The study was approved and we were granted permission to access patient records by the legal department, Capital Region of Denmark (p‐2023‐15194; 28 December 2023) and Team for Journal Data, the Capital Region of Denmark (R‐23069619; 19 December 2023).
2.4. Screening and Inclusion
One investigator (T.X.M.T.) screened the operating room surgical schedule in the electronic medical record, Sundhedsplatformen (Epic Systems Corporation, WI, USA), for potentially eligible patients. Final determination of eligibility occurred if the patient was transferred to the PACU after surgery. Eligible patients were approached by the investigator on arrival in the PACU, where written informed consent was obtained before study inclusion. For patients who were heavily sedated, values were recorded and consent was obtained when the sedation ceased.
2.5. Pain
Worst pain at rest during the first hour after PACU arrival constituted the x‐axis in the OPIAID Zone Tool. Pain intensity was assessed using the 11‐point Numeric Rating Scale (NRS). A designated investigator (T.X.M.T.) and the attending PACU nurse collected patient‐reported pain scores together on arrival to the PACU, 1 h after arrival, on referral to the surgical ward and whenever there was a need for rescue medication or an increase in pain intensity or ORADE burden during the PACU stay.
The literature provided no established NRS pain intensity cut‐offs suitable for defining the OPIAID Zone Tool [19, 20]. Therefore, pragmatic cut offs of 2, 4, 6 and 8 were prespecified.
We also explored a simplified version of the OPIAID Zone Tool based on a 4‐point Verbal Rating Scale (VRS; none, mild, moderate and severe). The VRS was therefore recorded simultaneously with the NRS at each pain assessment.
2.6. ORADEs
The worst measure of each ORADE during 0–1 h after PACU arrival was compounded into a composite score to assess the burden of ORADEs. This score constituted the y‐axis in the OPIAID Zone Tool. Nausea contributed 1–3 points according to patient‐reported severity (mild, moderate or severe), with one additional point assigned for vomiting. Sedation contributed 1–3 points according to the clinician‐assessed AVPU scale (V = 1, p = 2, U = 3) [21]. One point was assigned for each of the following ORADEs: patient‐reported itching, patient‐reported dizziness and clinician‐identified urinary retention in patients without a urinary catheter, spinal anaesthesia or active epidural analgesia. One point was also assigned for either hallucinations or confusion as assessed by the PACU nurse. Finally, respiratory depression contributed one point and was defined as either naloxone administration, a respiratory rate below 10 breaths/min or oxygen saturation below 90% that the PACU nurse considered possibly opioid‐induced (Table 1). The composite ORADE score ranged from 0 to 10 points. Although the theoretical maximum score was 12, values were capped at 10 because certain ORADE combinations were considered clinically very implausible (e.g., an AVPU score of P/U occurring together with confusion, hallucinations and severe nausea). This resulted in both the x‐ and y‐axes using 0‐ to 10‐point scales.
TABLE 1.
Composite ORADE score.
|
Composite ORADE score of 0–10 points (12 possible points; ≥ 10 will be rated as 10) |
|---|
| 1–3 points for self‐reported mild/moderate/severe nausea |
| 1–3 points for clinician‐reported sedation rated on the AVPU scale (V = 1, P = 2, U = 3) |
| 1 point for vomiting |
| 1 point for self‐reported itching |
| 1 point for self‐reported dizziness |
| 1 point for clinician‐reported urinary retention in patients without urinary catheter, spinal anaesthesia or active epidural analgesia |
| 1 point for either hallucinations or confusion as rated by the PACU nurse |
| 1 point for respiratory depression defined as either (1) naloxone use; (2) respiratory rate < 10 breaths/min counted by the attending nurse/clinician and perceived as possibly opioid‐induced or (3) oxygen saturation < 90%, which the PACU nurse perceives as possibly opioid‐induced |
2.7. Patient‐Perceived Health and Quality of Recovery in PACU
Patient‐perceived health was assessed using the Health Status Today (EQ Visual Analogue Scale [VAS]) adapted to reflect the patient's health status during the PACU stay. The EQ VAS is part of the validated patient‐reported outcome European Quality of Life 5 Dimensions 5 Levels Health Questionnaire (EQ‐5D‐5L) and measures health status on a 0–100 VAS [22]. Quality of Recovery was assessed using the Quality of Recovery Questionnaire for the PACU (QoR‐PACU version 1) [23]. We used a previously described Danish translation of the questionnaire [17].
2.8. PACU Discharge Readiness
Criteria for PACU discharge readiness in Denmark include an AVPU score of A or V; a respiratory rate of 10–20 breaths/min, with or without snoring; plethysmographic oxygen saturation ≥ 90%; systolic blood pressure 90–199 mmHg; a pulse rate of 50–120 beats/min; the ability to move the hands and flex the knees; none‐to‐mild pain or a VAS pain score ≤ 30 mm; none–mild nausea and a maximum aggregated score of four points across these physiological parameters [24]. Although these criteria define discharge readiness, the final decision to discharge the patient from the PACU is made at the discretion of the attending PACU nurse and anaesthesiologist. Time from PACU arrival to discharge readiness was used as a measure of PACU recovery.
2.9. The OPIAID Zone Tool
The OPIAID Zone Tool is intended as a composite outcome measure incorporating both pain and the degree of ORADE severity (Figure 1). These factors contribute to both the patient's perception and the organisation's evaluation of perioperative pain management quality, encompassing patient‐evaluated health status during the PACU stay and time to discharge readiness in PACU [6, 14, 15]. The OPIAID Zone Tool is based on the principle that different combinations of pain intensity and ORADE burden can represent a similar overall postoperative burden. Patients may therefore be assigned to the same OPIAID zone despite different combinations of pain and ORADEs.
FIGURE 1.
OPIAID Zone Tool (version 0.5). We hypothesised that lower zones will be associated with higher EQ VAS, higher QoR‐PACU scores and shorter time to PACU discharge readiness. The theoretical idea is that with increasing opioid doses (blue curved line), patients shift from having pain towards having pain relief and opioid‐related adverse events (ORADEs).
2.10. Outcomes
2.10.1. Primary Outcome
The primary outcome was the OPIAID Zone Tool (version 0.5) score.
2.10.2. Secondary Outcomes
EQ VAS, QoR‐PACU, length of PACU stay, NRS pain and the composite ORADE scale described in Table 1.
2.11. Statistical Analysis
2.11.1. Primary Analysis
The primary analysis evaluated whether increasing zones in the OPIAID Zone Tool (version 0.5) were associated with progressively worse EQ VAS, QoR‐PACU and time to PACU discharge readiness.
2.11.2. Exploratory Analyses
We repeated the primary analyses using the alternative OPIAID Zone Tool versions described below. These analyses were intended to explore whether different combinations of pain and ORADE constructs, weighting schemes and zone definitions would improve the association with the study outcomes. Given the small sample size and the inherent risk of overfitting, these analyses were considered hypothesis‐generating. They were performed with the intention to inform future optimisation of the OPIAID Zone Tool in a larger validation cohort.
A simplified OPIAID Zone Tool. We explored a simplified version of the OPIAID Zone Tool by replacing the NRS with VRS and categorising ORADE burden into four groups (0, 1–4, 5–8 and 9–12 points).
The full OPIAID Zone Tool. Here, we used NRS 0–10 for pain assessment and for ORADEs, we used the full ORADE scale as described above.
A vectorised version with the intention to assess whether measuring the vector length of the coordinate instead of zones.
- Alternative cut‐off versions, to assess if zones could be optimised. We revised the ORADE scale to reflect patient relevance based on data regarding ORADEs' negative impact on recovery in the PACU. These data were obtained from survey responses from PACU nurses (from a national survey) and from cohort studies of patients who had encountered ORADEs [25, 26]. This led to three versions of the OPIAID Zone Tool:
- Weighted scores with a maximum of 10‐to harmonise values in the XY‐scatter.
- Weighted scores normalised to a maximum score of 10‐to make it more generalisable across different populations with different max ORADE scores.
- Maximum ORADE adjustment with a factor of 1.25‐to make a generalisable cap.
Data‐driven versions. We sampled all options for combining pain and ORADEs into zones and visually assessed the 10 best‐performing.
Data were handled using R version 4.5.0 (R Core Team, Vienna, Austria). Categorical data were presented as numbers and percentages, whereas continuous data were presented as means and 95% confidence intervals (CIs) or medians with interquartile range (IQR), depending on data distribution. No data were imputed.
We investigated the association between outcomes (EQ VAS, QoR‐PACU and PACU discharge readiness) and covariates (e.g., zone in the OPIAID Zone Tool) using a multivariable linear regression model with procedure type as a fixed effect [17]. Model performance was primarily evaluated using R 2 as a goodness‐of‐fit measure, reflecting the proportion of variance in the outcome explained by the model. In addition, Akaike's information criterion (AIC) and Bayesian information criterion (BIC) were applied to compare competing models while penalising for model complexity; lower AIC and BIC values indicate a better balance between explanatory power and parsimony, with BIC imposing a stricter penalty for additional parameters. Superiority between models was further assessed using analysis of variance (ANOVA) based on an F‐test, with statistical significance defined as p < 0.05 to compare nested linear regression models and assess whether the more complex models provided a significantly better fit than the simpler model. The intra‐zone variance of the outcome of interest was explored visually using scatter plots. For the exploratory investigation of using vector length between (0, 0) and the XY‐coordinates in the OPIAID Zone Tool, we calculated the vector length and used this as a continuous covariate [17]. In the investigation into different zone definitions and ORADEs scoring systems, we calculated every possibility and defined the optimal axes and zone cut‐offs. We then took the visual feasibility of the 10 best‐performing models into account and chose the one with the most clinically applicable zones [17].
2.12. Protocol Violations
We initially planned to include 200 patients. However, the inclusion rate was lower than expected and the allocated funding for the investigator was insufficient to continue data collection. Therefore, the study was discontinued after the inclusion of 145 patients. This pilot study was based on a convenience sample with no formal sample size and while the smaller‐than‐planned sample size limits the precision of the estimates, it does not affect the planned external validation. The performance of the Zone Tool version 0.5 will be further explored in a pre‐planned external validation study using a prospectively collected cohort of 656 patients.
2.13. Use of AI
AI‐assisted tools were used for language refinement. The authors are fully responsible for the content.
3. Results
Of 1924 surgical procedures conducted at Copenhagen University Hospital—Bispebjerg in the study period on the days of inclusion, 341 were eligible and 145 (43%) were included (Figure 2). The mean age was 50 years; 48% were female; 18% were ASA 3–4; patients were equally distributed between orthopaedic and abdominal surgery (Table 2). Intraoperatively, 104 (72%) received morphine, 47 (32%) received sufentanil, 6 (4%) received oxycodone and 2 (1%) received fentanyl as analgesia before emergence from anaesthesia. Intraoperative IME was a median of 20 (IQR: 15–25). As intraoperative antiemetic prophylactics, 99% and 90% received dexamethasone and ondansetron, respectively. Fifty‐five patients received a peripheral nerve block in addition to general anaesthesia. No patients received neuraxial anaesthesia. The mean worst pain score 0–1 h postoperatively was 4.9 (95% CI: 4.4–5.3). The mean ORADE score was 1.52 (95% CI: 1.28–1.75) with a maximum of 6. Dizziness was the most frequent ORADE, reported by 50% of patients. Confusion occurred in 24% of patients. Respiratory depression was observed in 23% of patients, but none were administered naloxone. Mild nausea was reported by 22% of patients and 72% did not experience nausea at all. None of the patients experienced hallucinations (Table 3). There were no missing data points.
FIGURE 2.
CONSORT diagram.
TABLE 2.
Baseline characteristics (n = 145).
| Variable | Overall |
|---|---|
| Age, mean (95% CI) | 50.45 (47.02–53.88) |
| Sex, male, n (%) | 76 (52.4%) |
| BMI, mean (95% CI) | 26.74 (25.83–27.65) |
| Weight, mean (95% CI) | 81.52 (78.34–84.70) |
| Smoking status, n (%) | |
| Current | 29 (20.0%) |
| Never | 71 (49.0%) |
| Former | 45 (31.0%) |
| ASA physical status, n (%) | |
| ASA I | 49 (33.8%) |
| ASA II | 70 (48.3%) |
| ASA III+ | 26 (17.9%) |
| Surgical speciality, n (%) | |
| Gastrointestinal surgery | 75 (51.7%) |
| Orthopaedic surgery | 70 (48.3%) |
| Type of surgery, n (%) | |
| Anterior cruciate ligament reconstruction | 32 (22.1%) |
| Elective total hip arthroplasty (THA) | 10 (6.9%) |
| Hip arthroscopy | 5 (3.4%) |
| Inguinal hernia repair | 21 (14.5%) |
| Laparoscopic appendectomy | 3 (2.1%) |
| Laparoscopic cholecystectomy | 30 (20.7%) |
| Laparoscopic hemicolectomy | 11 (7.6%) |
| Laparoscopic rectum or sigmoid resection | 10 (6.9%) |
| Total knee arthroplasty | 4 (2.8%) |
| Trochleoplasty | 19 (13.1%) |
| Regional blockade, n (%) | 55 (37.9%) |
| Preoperative pain, n (%) | 65 (44.8%) |
| EQ‐VAS, mean (95% CI) | 77.46 (74.42–80.51) |
| QoR PACU, mean (95% CI) | 9.12 (8.32–9.93) |
| PACU length of stay (min), mean (95% CI) | 108.24 (99.47–117.01) |
TABLE 3.
Pain and ORADE characteristics (n = 145).
| Variable | Overall |
|---|---|
| Pain (NRS), mean (95% CI) | 4.89 (4.44–5.34) |
| Nausea, n (%) | |
| 0 | 105 (72.4%) |
| 1 | 32 (22.1%) |
| 2 | 7 (4.8%) |
| 3 | 1 (0.7%) |
| Sedation, n (%) a | 0 (0.0%) |
| Confusion, n (%) | 35 (24.1%) |
| Dizziness, n (%) | 72 (49.7%) |
| Itching, n (%) | 20 (13.8%) |
| Respiratory depression, n (%) | 34 (23.4%) |
| Naloxone administration, n (%) | 0 (0.0%) |
| Hallucinations, n (%) | 0 (0.0%) |
Sedation and confusion were inadvertently registered in the same database field. As no patients had an AVPU score below V or experienced sedation and confusion simultaneously, the registration error did not affect the composite ORADE score, although the two outcomes could not be distinguished retrospectively.
3.1. Primary Outcome
The distribution across OPIAID Zone Tool (version 0.5) categories was Zone 0: 20 (13.8%), Zone 1: 10 (6.9%), Zone 2: 32 (22.1%), Zone 3: 27 (18.6%), Zone 4: 29 (20.0%) and Zone 5: 27 (18.6%) (Figure 3). Overall, patients were broadly distributed across zones without clear clustering but with a tendency towards the pain‐dominant side rather than the ORADE‐dominant side.
FIGURE 3.
OPIAID Zone Tool (version 0.5) reproduced from the published protocol [17]. Cohort distribution (n = 145) and association with EQ VAS, QoR‐PACU and length of PACU stay.
3.2. Secondary Outcomes
For EQ VAS, the OPIAID Zone Tool showed the best model performance, with the lowest AIC and BIC and the highest explained variance (R 2 = 0.39), followed by ORADEs and then pain (Figure 3).
For QoR PACU, ORADEs performed best, with the lowest AIC and BIC and the highest R 2 (0.37), followed by the OPIAID Zone Tool (R 2 = 0.35) and then pain.
For PACU length of stay, the OPIAID Zone Tool demonstrated the best performance, with the lowest AIC and BIC and the highest explained variance (R 2 = 0.50), followed by pain and then ORADEs.
Aggregating these findings, the OPIAID Zone Tool showed the best model performance.
3.3. Exploratory Analyses
We evaluated five preplanned alternative versions of the OPIAID Zone Tool: (1) a simple representation using a heatmap of Likert‐scale pain and ORADE scores; (2) a vectorised approach, defined as the Euclidean distance from the origin (0, 0) to the observed point in the zone space; (3) a weighted score with a cap at 10, where ORADEs were calculated as in the original model but truncated at a maximum value of 10; (4) ORADE normalisation to a 0–10 scale, where the maximum ORADE score was rescaled to 10 and all values adjusted proportionally and (5) an ORADE‐adjusted model applying a scaling factor of 1.25 to the ORADE score. The ‘ORADEs normalised to 10’ version outperformed the other (EQ VAS R 2 = 0.40, QoR‐PACU R 2 = 0.35, PACU LOS R 2 = 0.51) (Figure S2).
We simulated 66,000 potential models with different zone divisions to explore data‐driven models. The best‐performing of these models outperformed the OPIAID Zone Tool (version 0.5) (EQ VAS R 2 = 0.44, QoR‐PACU R 2 = 0.42, PACU LOS R 2 = 0.50) (Supplemental Material S3, 9 + 13–18).
The ‘weighted scores normalised to 10’ version outperformed the other (EQ VAS R 2 = 0.40, QoR‐PACU R 2 = 0.35, PACU LOS R 2 = 0.51).
4. Discussion
This study provides early proof of associations between core recovery outcomes and the OPIAID Zone Tool. The tool is both a composite measure of postoperative pain and ORADEs and a visual display of the relationship between these outcomes in a population. Compared with separate assessments of pain and ORADEs, the OPIAID Zone Tool version 0.5 had stronger associations with EQ VAS, QoR‐PACU and time to PACU discharge readiness. Patients were broadly distributed across zones without clustering, suggesting that the tool captures a continuous spectrum of postoperative burden.
Although the theoretical ORADE score ranges from 0 to 12, no patient had a score above 6. The ORADE axis was therefore displayed on a 0–10 scale to match the NRS pain scale without affecting patient classification or the distribution across zones. The relative weighting of pain and ORADE burden remains an important aspect of the tool's future development. In this study, we already explored several alternative weighting schemes. Although these analyses were hypothesis‐generating and susceptible to overfitting, a hypothetical version with weighted ORADE scores by normalising them to 10 showed slightly stronger associations with EQ VAS, QoR‐PACU and time to PACU discharge readiness than the primary 0.5 version. This suggests that refinement of the relative weighting between pain and ORADE burden may improve the performance of the OPIAID Zone Tool.
The OPIAID Zone Tool requires several conceptual choices regarding the relative importance of pain intensity and individual ORADEs, the weighting of different adverse events and the definition of zone boundaries. These choices were based on clinical judgement and were, to some extent, arbitrary. Future validation studies should evaluate alternative weightings, including the exploratory versions from this study, to optimise the association with clinically relevant outcomes and better reflect the overall postoperative pain and adverse event burden.
4.1. The OPIAID Zone Tool in Light of Existing Outcomes and Recovery Scores
Several composite instruments have been developed to integrate pain, ORADEs and other aspects of postoperative recovery into a single score. However, such summary scores do not pinpoint whether suboptimal recovery is primarily driven by inadequate analgesia, excessive ORADEs or both. One example is the Quality of Recovery‐15 (QoR‐15), which is extensively validated across 22,847 patients in 16 countries, demonstrating excellent reliability (Cronbach's α = 0.85) and discriminant validity. It is recommended for perioperative clinical trials [27, 28] but does not highlight the balance between pain and ORADEs. The Overall Benefit of Analgesia Score (OBAS) combines pain intensity, pain satisfaction and some ORADEs into a validated score that shows higher resolution of treatment effects than pain scores alone [29]. The Opioid‐Related Symptom Distress Scale (OR‐SDS) assesses 12 opioid‐related symptoms across the dimensions of frequency, severity and bothersomeness and has been validated in both orthopaedic and general surgical populations [30]. Recently, the IMI‐PainCare PROMPT consortium recommended OR‐SDS assessment in perioperative pain research [31]. Overall, existing recovery instruments primarily quantify how well the patient recovers after surgery in an overall assessment of the postoperative recovery phase. In contrast, the OPIAID Zone Tool was developed to evaluate the balance between analgesic efficacy and ORADEs, which represent the two central targets of perioperative analgesic treatment. Instead of incorporating downstream recovery outcomes into the Zone Score itself (mobilisation, discharge readiness, quality of recovery and patient‐perceived health), the OPIAID Zone Tool focuses on the treatment balance that we hypothesise to drive these outcomes. Further, interpretation of a population's distribution in the two‐dimensional visual tool may help identify whether postoperative outcomes are primarily limited by inadequate analgesia, excessive opioid‐related harms or a balance of both. This information could guide optimisation of multimodal analgesic regimens and subsequently be used to evaluate whether changes in perioperative analgesic strategies produce the anticipated shift in OPIAID Zone Tool distribution. It may also facilitate comparison of analgesic regimens or study groups in clinical research.
In the next development stages, we plan to test whether and how the OPIAID Zone Tool can provide information beyond the summary score in the two‐dimensional visualisation. Here, we will focus on how different multimodal analgesic pathways and surgical procedures are associated with distinct zone profiles characterised by clustering towards pain‐dominant or ORADE‐dominant sides. Moreover, we will test associations with mobilisation outcomes.
Meta‐analyses may be another potential application of the OPIAID Zone Tool, where pain and ORADEs are currently reported as separate outcomes [11, 12]. These intervention effects may be divergent in terms of superiority, with improved analgesia and increased ORADEs. Plotting each study into the OPIAID Zone Tools visual presentation or even applying individual participant data where available, could help visualise the joint distribution of pain and ORADEs across studies and provide a more integrated comparison of the clinical consequences of an intervention or an overview of head‐to‐head comparisons between different interventions.
4.2. Strengths and Limitations
This was a pilot study that sought to evaluate the logistics, methodology and feasibility around the development of the OPIAID Zone Tool. Therefore, there are some limitations that need to be mentioned. First, we explored multiple versions of the OPIAID Zone Tool, which entails a large risk of overfitting. Second, it was a single‐centre study in which we included 145 of the protocolled 200 patients and though it was a convenience sample, it must/could have reduced the power of the study. However, before this development study, we preplanned the 656‐patient validation study for further refinement of the OPIAID Zone Tool (the inclusion and data extraction were completed in 2025) [26]. Third, sedation and confusion were inadvertently registered in the same database field and could therefore not be distinguished retrospectively. However, no patient had an AVPU score below V and no patient experienced both sedation and confusion simultaneously. Consequently, the registration error did not affect the calculated composite ORADE score or the resulting OPIAID Zone classification.
Regarding generalisability to other settings and populations, perioperative analgesia strategies are very different between hospitals and countries, which will be a barrier towards general use. Excluding chronic opioid users is a limitation and this patient group should be included in follow‐up studies.
Patients differ in their susceptibility to ORADEs and some may experience adverse effects despite low opioid doses. While this interindividual variability is not captured by the current Zone Tool, observations in the outer zones may help identify clinically distinct patient subgroups for future investigation.
4.3. Future Directions
Exploratory analyses indicate potential for refinement. Alternative specifications, particularly normalisation of ORADEs, showed modest improvements and data‐driven models further increased explained variance. Thus, the OPIAID Zone Tool (version 0.5) represents a clinically interpretable starting point, but not an optimised model and further development towards a refined version 1 with prospective validation is warranted. The tested versions will be carried forward to further refinement and designation of the OPIAID Zone Tool (version 1) in a cohort of 656 patients from 5 hospitals [26].
Based on the combination of the pilot and primary cohorts, we will explore the relationship between intraoperative opioid dosing and zone placement, including potential dose optima, while exploratory analyses will assess whether surgical procedures cluster in distinct risk zones. This validation will provide an initial real‐world assessment of the tool's clinical and research utility. Future studies should also investigate the correlation between the Zone Tool and mobilisation outcomes because mobilisation is another dimension of postoperative care that has a strong impact on patient recovery, but which is not included in the configuration of the Zone Tool.
5. Conclusion
The OPIAID Zone Tool (version 0.5) is a novel approach that combines postoperative pain and ORADEs into a single visual framework. It was associated with patient‐centred outcomes and demonstrated stronger associations than pain intensity and ORADEs assessed separately, although a risk of overfitting cannot be ruled out. Further refinement and prospective external validation are planned to optimise the tool and confirm its clinical utility.
Author Contributions
A.P.H.K. conceived the idea of the OPIAID Zone Tool and managed the overall study design. A.P.H.K., M.H.O. and T.X.M.T. planned the study. T.X.M.T. included all patients and collected all data. M.H.O. and A.P.H.K. made visuals and models. A.P.H.K. wrote the first draft. T.H.L., C.S.M. and O.M. contributed with critical details regarding outcomes and methodology. All authors critically revised the manuscript and take responsibility for the content.
Funding
A.P.H.K. received funding for part‐time release to conduct research from the Bispebjerg Research Foundation and the Region Hovedstaden Research Fund. T.X.M.T. received funding for salary from the Bispebjerg Research Foundation.
Ethics Statement
The Danish National Center for Ethics concluded that the study did not require ethical approval (F‐23064248; 24 October 2023). The study was approved and we were granted permission to access patient records by the legal department, Capital Region of Denmark (p‐2023‐15194; 28 December 2023) and Team for Journal Data, the Capital Region of Denmark (R‐23069619; 19 December 2023).
Consent
Written informed consent was obtained for all participants.
Conflicts of Interest
Christian S. Meyhoff has founded a start‐up company, WARD24/7 ApS, with the aim of pursuing the regulatory and commercial activities of the WARD project (Wireless Assessment of Respiratory and Circulatory Distress, a project developing a clinical support system for continuous wireless monitoring of vital signs). WARD24/7 ApS has obtained a licence agreement for any WARD‐project software and patents. One patent has been filed: ‘Wireless Assessment of Respiratory and Circulatory Distress (WARD), EP 21184712.4 and EP 21205557.8’. The other authors declare no conflicts of interest.
Supporting information
Table S1: Overview of data collected during different time points for an included patient.
Figure S2: Performance of alternative versions of the OPIAID Zone Tool.
Supplementary Material S3: Full statistical report.
Acknowledgements
The authors have nothing to report.
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Table S1: Overview of data collected during different time points for an included patient.
Figure S2: Performance of alternative versions of the OPIAID Zone Tool.
Supplementary Material S3: Full statistical report.
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.